Improving schema understandability for semantic integration

数据库非常复杂;典型的数据库可以在数百个表中存储数据，并且可以在表之间包含数百个引用。 数据在表中的布局以及它们之间的引用称为模式。 学习这些复杂模式的细节需要大量的时间。 由于数据源在各个组织之间共享，以及用户试图让他们的应用程序做一些他们最初没有设计的事情，这个问题变得更加严重。考虑以下两种情况： (1)用户正在集成多个应用程序中的土木工程数据，包括CAD模型和项目调度。 这些应用程序中的数据可以通过许多不同的标准导出。 为了集成数据，用户必须首先选择要导出的标准，然后弄清楚如何理解数据是如何导出的。 (2)最终用户可以访问生成报告的数据库应用程序。 最终用户要求数据库程序员更改应用程序以访问比最初可访问的更多的信息。 程序员以前从未见过应用程序，但现在必须扩展应用程序以访问新数据。 这将要求程序员理解后端数据库中的数据是如何存储的，以便编写新的查询。 这两种情况都没有得到现有方法的充分帮助。 我建议提高图式理解。其目标是帮助用户在各种场景中（包括上述场景）更好地利用他们首次遇到的现有模式，无论是扩展他们对当前应用程序的理解，还是尝试决定如何将数据导出到标准模式（这是具有挑战性的，因为相关数据可能分散在标准模式中，使其难以理解），或者选择数据应该遵循的标准模式。

Databases are very complex; a typical database can store data in hundreds of tables and can contain hundreds of references between tables. The layout of the data into tables and references between them is referred to as a schema. Learning the details of these complex schemas requires significant time. This problem is exacerbated by data sources being shared across organizations, and users attempting to make their applications do something for which they were not originally designed. Consider the following two scenarios: (1) A user is integrating civil engineering data across a number of applications, including CAD models and project scheduling. The data in these applications can be exported via a number of different standards. In order to integrate the data, the user must first choose which standard to export from and then figure out how to understand how the data has been exported. (2) An end user has access to a database application that generates reports. The end user asks the database programmer to change the application to access more information than was originally accessible. The programmer has never seen the application before, but now must extend the application to access new data. This will require the programmer to understand how the data in the back-end database is stored well enough to write the new queries. Neither of these scenarios is adequately helped by existing approaches. I propose to improve schema understanding. The goal is to help users in a variety of scenarios including those above to make better use of the existing schemas that they are encountering for the first time, whether it is extending their understanding of a current application, trying to decide how to export their data to a standard schema (which is challenging since related data may be scattered across the standard schema, rendering it incomprehensible), or choosing a standard schema to which the data should adhere.